Robotic systems and methods in prediction and presentation of resource availability

ABSTRACT

Systems and methods to predict and present availability and value of retail spaces in shopping malls. Robots are dispatched to temporary retail spaces to collect at least a portion of operation data stored in a database with leasing data of temporary retail spaces in a mall, tenant coordination data, and subscriber data. A web-based application predicts availability of the temporary retail spaces in the mall based on the leasing data, the tenant coordination data, and the operation data. The web-based application includes an interactive plan of the mall as a user interface for subscribers to access data related to the temporary retail spaces, and process applications for leasing the temporary retail spaces.

RELATED APPLICATIONS

The present application claims the benefit of the filing date of Prov.U.S. Pat. App. Ser. No. 62/218,172, filed on Sep. 14, 2015, the entiredisclosure of which application is hereby incorporated herein byreference.

The present application relates to U.S. Pat. App. Ser. No. 14/946,635,filed Nov. 19, 2015, the entire disclosure of which application ishereby incorporated herein by reference.

FIELD OF THE TECHNOLOGY

At least some embodiments of the present disclosure relate to robotshaving indoor location determination devices to guide their movements ina building structure, and their usages in collecting information for theprediction of the availability of resources, such as spaces.

BACKGROUND

U.S. Pat. App. Pub. No. 2009/0149992 discloses a robot capable oftraveling within a predetermined pathway area.

U.S. Pat. App. Pub. No. 2010/0094463 discloses a robot having a positionrecognition section that recognizes a current position of the robotwithin a guide zone. The robot is controlled to move to each of guidelocations in the guide zone. At each of the guide locations, the robottransmits contents information corresponding to the guide location to amobile terminal held by a person to be guided near the robot.

U.S. Pat. No. 7,860,647 discloses a traffic condition prediction tableused to predict vacancy of a parking lot as an accommodating facilityfor presentation on a navigation device.

U.S. Pat. App. Pub. No. 20140365251 discloses a vacancy rate calculationapparatus for tables in a restaurant.

The disclosures of the above discussed patent documents are herebyincorporated herein by reference.

BRIEF DESCRIPTION OF THE DRAWINGS

The embodiments are illustrated by way of example and not limitation inthe figures of the accompanying drawings in which like referencesindicate similar elements.

FIG. 1 shows a robot according to one embodiment.

FIG. 2 illustrates an application of a robot according to oneembodiment.

FIG. 3 shows a robotic system according to one embodiment.

FIG. 4 shows a robotic method according to one embodiment.

FIG. 5 shows a system configured to predict and present availability ofresources according to one embodiment.

FIG. 6 shows a system to provide availability prediction and valueestimation according to one embodiment.

FIG. 7 shows a method to provide availability prediction and valueestimation according to one embodiment.

FIG. 8 shows a data processing system that can be used to implement somecomponents of a robotic system according to one embodiment.

DETAILED DESCRIPTION

The following description and drawings are illustrative and are not tobe construed as limiting. Numerous specific details are described toprovide a thorough understanding. However, in certain instances, wellknown or conventional details are not described in order to avoidobscuring the description. References to one or an embodiment in thepresent disclosure are not necessarily references to the sameembodiment; and, such references mean at least one.

FIG. 1 shows a robot according to one embodiment.

In FIG. 1, a robot (101) includes a base (105), a body (111), a touchscreen (103) and a camera (109). In one embodiment, the robot (101) isprogrammable to travel within an area, such as a shopping mall, captureinformation and/or photo images, provide a user interface forinteraction, and/or transport items.

In FIG. 1, the camera (109) is mounted directly on the body (111). Insome alternative embodiments, the camera (109) is integrated with thetouch screen (103). For example, the touch screen (103) can beimplemented using a tablet computer having a camera (109) and running anoperating system for mobile devices; and a mobile application running inthe tablet computer is configured to control the operations of the robot(101). In some embodiments, the computer configured to control theoperations of the robot (101) is integrated within the body (111) or thebase (105). In some embodiments, the robot (101) includes a wirelesscommunications device (e.g., an antenna and a transceiver for a wirelesslocal area network, or a wireless personal area network) for acommunication connection to a remote server.

In FIG. 1, the robot (101) has a touch screen (103) within which acontroller of the robot (101) may be installed. Alternatively, thecontroller of the robot (101) may be disposed within the body (111) orthe base (105).

In FIG. 1, the base (105) of the robot (101) includes a moving mechanism(113) controllable to move the robot (101) in a pathway area, such asthe hallways in a shopping mall, or a sidewalk of a strip mall. Forexample, the moving mechanisms disclosed in U.S. Pat. App. Pub. No.2009/0149992 or 2010/0094463 can be used, the disclosure of which isincorporated herein by reference.

In one embodiment, the moving mechanism (113) in the base (105) of therobot (101) is configured to rotate the robot (101) as a whole about avertical line at a location to allow the camera (109) to take a 360degree photo image of the surrounding.

In one embodiment, the base (105) and the body (111) are configured toallow the body (111) to rotate about a vertical line passing through thecenter of the base (105). Thus, the base (105) can be controlled to stayat location; and the body (111) can be controlled to rotate about thevertical line to take a 360 degree photo image of the surrounding. In afurther embodiment, the camera (109) is mounted on a track on the body(111) and configured to move alone the track to take a 360 degree photoimage of the surrounding.

The 360 degree photo image can be obtained via a camera taking aplurality of photo images while rotating about the vertical line andthen digitally stitching the images together to form a photo imagehaving a 360 degree view of the surrounding at the location of the robot(101).

Alternatively, the camera may capture one or more vertical lines ofimage pixels at a time while the robot (101) rotates about the verticalaxis. The vertical lines captured at different time instances while therobot (101) is at different angles with respect to the vertical axisform an image having the 360 degree view of the surrounding.

In one embodiment, the robot (101) (or a server) is configured toanalyze the image to extract information about the location, such as theadvertisements, notices and/or deals posted on the store front of aretailer, the number of customers in the surrounding area, etc.

In one embodiment, the robot (101) further includes storage spaces (107)configured to carry items for delivery by the robot (101). Items storedin the storage spaces (107) can be secured with a locked door or latchto prevent theft, unauthorized access, temper, etc.

In FIG. 1, the robot (101) has a connector (119) configured to beconnected with the receptacle (117) of the dock station (137) to providea wired connection to charge the battery of the robot (101) and/orprovide a communication link for transferring data and/or instructionsbetween the robot (101) and a server (e.g., as further illustrated inFIG. 3).

In one embodiment, the robot (101) includes an indoor positiondetermination system that determines the position of the robot (101)within a building structure, such as a shopping mall. The controller ofthe robot (101) also includes map data of the shopping mall to guide therobot (101) to one or more locations programmed into the robot via awired or wireless communication connection.

FIG. 2 illustrates an application of a robot according to oneembodiment.

In FIG. 2, the robot (101) is configured to move inside a shopping mall.The robot (101) is instructed to take a 360 degree photo image of thesurrounding at a location near a store front (125) and/or otherlocations near or in the store. For example, the store front (125) mayhave a posting (121) announcing a deal, such as a sales event, adiscount offer, etc. The 360 degree photo image captured using thecamera (109) of the robot (101) includes an image of the posting (121).

In one embodiment, optical character recognition (OCR) is performed onthe image to extract the content of the posting. The postings may befiltered based on keywords, such as “sale” or “off”, to obtain postingsof a particular type, such as discount offers.

In one embodiment, the posting (121) may include a bar code (123); andthe image of the bar code (123), as captured in the 360 degree photoimage, is processed to determine the content of the bar code (123). Forexample, the bar code (123) may provide information about the posting(121) and/or an address of a web page from which further informationabout the posting (121) can be obtained.

Thus, the robot (101) can be instructed to move from a store front toanother in a shopping mall, and take photo images that may contain thepostings provided by the stores in the shopping mall. The images areprocessed by the robot (101) (or a server) to extract identify postingsof interest, such as discount offers.

In one embodiment, the robot (101) is used to bring consumers,retailers, and technology partners together in ways that enhance theshopping experience. Specifically, the robot (101) can be used tocapture data to allow customers to find and purchase products.

For example, the robot (101) can be used to make product catalogsavailable for search on web and mobile, such as the integration of realtime inventory feeds from retailers to offer product availability foreach store. The robot (101) can be used to capture offer and productavailability information using the camera (109) mounted on the robot(101).

For example, the robot (101) can further be used to assist productpurchase and fulfillment. The robot (101) can be used to deliver goodsto a central location for fulfillment. For example, in services such ashands free shopping and centralized fashion lounge, the customers cantry on clothing from several different retailers in one location, afterthe robot (101) collects the goods from different retailers in ashopping mall and delivery the collected goods to the current retailerlocation of the customer.

For example, a customer may order the goods from retailers in a shoppingmall via phone or Internet; and the robot (101) can be used to collectthe goods from the retailers and transport the goods to a logisticspartner which further delivers the goods to the customer. Alternatively,the collected goods can be placed in a centralized pickup location inthe shopping mall, where the customer can pick up the goods ordered fromdifferent retailers in the mall.

For example, when the robot (101) visits a retailer in a shopping mall,a person in the retailer store may interact with the robot (101) onbehalf of the retailer. The touch screen (103) provides a user interfacethat communicates to the persons items to be placed inside the storagespace (107) of the robot (101) and/or retrieved from the storage space(107). Thus, the robot (101) can transport goods from and/or to theretailer.

Further, the robot (101) may receive offers and/or product inventoryinformation from the representative of the retailer. For example, acomputing device of the representative (e.g., a smart phone, a tabletcomputer, a computer having a dock station) can be used to transmit theinformation to the robot (101) via a wireless or wired connection.

The robot (101) may automatically obtain certain offers and/or productinventory information via the camera (109) taking photo images ofpostings inside the store and/or the store front of the retailer.

In some embodiments, the robot (101) takes still images and/or videoimages of the retailer location to provide an updated feed of thearrangement and display of goods in the retailer store. Thus, the stillimages and the video images can be organized as a virtual tour of theretailer store accessible via internet.

In one embodiment, a user may use a mobile computing device (e.g., asmart phone, a digital media player, a tablet computer) to do “HandsFree Shopping” in which the user does not have to carry the items to bepurchased and/or have been purchased around the shopping mall. The usermay use the mobile computing device to select the items of interest forpurchase. The mobile computing device (e.g., having a mobile applicationrunning therein) communicates the list of items purchased by the user tothe computing system of the retailer (or a centralized server for theshopping mall). Based on the list of items received from the mobilecomputing device, the robot (101) travels to the stores in the mall,collects from the stores the items purchased by the user, and transportsthe items at a convenience location for pickup, such as in a pickup areain the parking lot.

In one embodiment, the robot (101) is used to capture images of offlineinformation for the indexing of the offline information in the realworld. For example, the robot (101) can be used to capture various typesof data, from product information and availability to safety andsecurity hazards within the shopping mall.

In one embodiment, the robot (101) has a cellular communicationstransceiver integrated within the touch screen (103), or disposed in thebody (111). A communication link provided by the cellular communicationstransceiver can be used for the communication between the robot (101)and a remote server to process images, retrieve data, control themovement of the robot (101), and/or provide access to the storage spaces(107).

In one embodiment, the robot (101) has a position determination systemconfigured to determine its position inside the shopping mall. The robot(101) is configured to identify the retailer stores based on itslocation within the shopping mall and/or beacon signals from the devicesdisposed in the retailer stores.

The robot (101) includes a wireless local area network transceiver(e.g., a WiFi transceiver). The robot (101) can be used to measure thesignal strength of access points for the wireless local area networkswithin the shopping mall and generate a heat map of WiFi strength.

In one embodiment, the robot (101) is configured to perform autonomousscheduling of mapping and docking, without assistance from humans. Forexample, the robot (101) is programmed to un-dock at a definedfrequency, collect/record mall data, re-dock and upload new content tobe consumed via API remotely.

In one embodiment, the robot (101) includes a reader for radio frequencyidentification (RFID) tags. The robot (101) is configured to move intothe retailer stores to scan RFID to obtain availability informationitems inside the store. For example, the scanning of the RFID tags allowthe robot (101) to determine the presence of a particular item that isavailable for purchase at a particular location within a particularretailer store. The information is indexed for search, such that a usercan quickly locate the item for inspection.

In one embodiment, the robot (101) includes a personal area networktransceiver (e.g., Bluetooth transceiver) to perform a wireless dockingconnection with a dock station (137) when the robot (101) is with apredetermined distance to a docking station. The robot (101) may alsomove around the mall to measure Bluetooth signals and/or detectBluetooth devices within the mall and correlate the detectedsignals/devices with the locations of the robot (101) at the time of thedetection to generate a map of Bluetooth signals/devices within themall.

In some embodiments, the robot (101) also includes a user interface fora customer to search for product availability information, reserveproducts, inspect a map of the mall, and obtain instructions to aparticular location of a particular retailer where an item of interestto the user is located.

FIG. 3 shows a robotic system according to one embodiment.

In FIG. 3, an intranet (131) interconnects one or more dock station(e.g., 137), a server (139), and a database (141). The database (143)stores location data (143) (e.g., a digital map of the shopping mall, acommercial district), and camera data (145) uploaded from the robots(101).

The robots (101) are programmed to travel within a predetermined area(the shopping mall, a commercial district) autonomously and capturecamera data (145) using their cameras (109). The camera data (145) islocation tagged for correlation with the retailer locations identifiedin the location data (143).

In one embodiment, the robot (101) has a memory configured to store thecamera data (145) before the data is updated to the database (141) viathe dock station (137). A robot (101) may connect with the dock station(137) via a wired connection (e.g., via a USB connector) or a wirelessconnection (e.g., via Bluetooth or WiFi).

In FIG. 3, the server (139) provides a user interface (e.g., via a webserver or a mobile application) that allows the users of the userdevices (149, . . . , 151) to access the camera data (145).

For example, the 360 degree still or video images captured by the robot(101) allows a user of the user device (149) to view the shopping mallthrough the camera (109) of the robot (101) and thus obtain a virtualtour of the shopping mall. In one embodiment, the user interface isconfigured to receive instructions from a user to approach one of a setof authorized locations within the shopping mall to obtain a still imageor a real time video feed from the camera (109) of the robot (101). Thereal time video, when presented via a virtual reality display device,provides a virtual reality experience in the shopping mall from a remotelocation. Thus, the robot (101) becomes a virtual representative of theuser in the real world shopping mall, where the user may explore themerchandises provided in the shopping mall and make selections andpurchases. A representative of a store may assist the robot (101) incompleting certain operations, such as picking up an item forinspection, and purchase. The robot (101) transports the purchased itemsto an centralized location for shipping to the customer. Optionally, thecustomer may choose to travel to the centralized location to pick up thepurchased items.

Further, in one embodiment, the server (139) (or the robot (101))processes the camera data (145) to obtain postings (121) provided in aprinted form on certain surfaces within the mall. For example, thediscount offers are recognized via OCR and/or bar code; and thus, adiscount offers can be communicated to the user devices (151) in variousforms, such as advertisements, search results, a list of offers forbrowsing, etc.

FIG. 4 shows a robotic method according to one embodiment. For example,the method of FIG. 4 can be performed in a system illustrated in FIG. 3,using a robot (101) illustrated in FIG. 1 in an environment illustratedin FIG. 2.

In one embodiment, a robotic system is configure to: provide (201) arobot (101) having a camera (109); instruct (203) the robot (101) totravel within a predetermined area; capture (205) images within thepredetermined area using the camera (109) of the robot (101); correlate(207) the images with predetermined locations within the predeterminedareas; generate (209) electronic content in associated with thepredetermined locations based on an analysis of the images; and provide(211) the electronic content via a website.

FIG. 5 shows a system configured to predict and present availability ofresources according to one embodiment.

In one embodiment, the system of FIG. 5 provides a platform for securingshort-term leases for temporary retail marketplaces in a shopping mall.It can be used to meet the need for leasing temporary retail spaces in ashopping mall in a structured and profitable way. There is currently noformalized method in the retail leasing market that allows for potentialtenants to connect with a temporarily-available or ‘pop-up’ retailspace.

The system of FIG. 5 creates a marketplace for pop-up retail space byautomatically predicting future, temporary vacancies and filtering thatdata into a platform that is accessible by external subscribers. Theplatform allows subscribers to view available space but also to makeoffers and enter into agreements in a streamlined way, without the useof a real estate broker.

In one embodiment, the system of FIG. 5 includes a subscriptionmechanism and a marketplace tool that acts as a customer database,building profiles on prospective retailers and generating leads beyondthe scope of traditional brokerage-based methods.

In one embodiment, the system of FIG. 5 includes an Enterprise ResourcePlanning tool to aggregate, correlate and predict future temporaryvacancies and the use of the subscription service to publicly offertemporary retail space for lease.

In one embodiment, the database (141) and the server (139) includes anEnterprise Resource Planning Tool (ERP); and a pop-up retail marketplace(PRM) is a module plugged in the Enterprise Resource Planning Tool (ERP)to aggregate data from the three departments: Leasing, TenantCoordination, and Operations, into a single user interface. The database(141) provides a centralized location for leasing data (223), tenantcoordination data (221), operation data (225), market data (227) andsubscriber data (229).

In one embodiment, the leasing data (223) includes sales brochures,development plans, lease terms and exhibits, financial and lease status;the tenant coordination data (221) includes lease plans, tenant designsubmissions, schedules, project status and approvals; the operation data(225) includes Automated Clearing House (ACH) data for recurringpayments, monthly statements and current balance, archive of anycorrespondence between tenant and landlord, retailer sales, leaseviolations, emergency contact information, before/after hours request,maintenance requests, tenant handbooks, certificate of insurance,storefront photos, etc.; and the marketing Data (227) includes socialmedia request, marketing tools, contact information, newsletters.

In FIG. 5, the server (139) is configured to provide an interactive plan(231) as a user interface to access the ERP data.

For example, the user may use the user interface to select a shoppingmall to see the plan of the shopping mall. Data of each individualretailer in the shopping mall is saved in association with the plan ofthe shopping mall. The user interface provides the user with the optionsto: manually select individual items of data related to individualretailers; correlate individual data across multiple retail spaceswithin the plan of the shopping mall; select multiple data fields acrossmultiple retail spaces within the plan of the shopping mall; and/orcorrelate multiple data results against the remainder of the portfolio.

Using data from the database (141) of the Enterprise Resource Planningtool, a Pop-Up Retail Marketplace application is implemented as aweb-based application hosted on the server (139), accessible via a webpage online or a mobile application. This application allows the userto: correlate against lease start date, or renewal date for any newlease on same space; identify all leases across the portfolio that aredue to expire within the next 6-12 months; if a retail space is subjectto new lease, correlate against tenant design progress and schedule;send results notice to leasing executive for verification, where theleasing executive is required to verify results; correlate the resultsagainst the progress of new tenants or renovations within the retailspace; feed that data to a marketplace that connects retailers lookingfor a pop-up store opportunity, with vacancies across the mallportfolio; vet subscribers at different levels through thesystem/people; and strategically show temporary openings in accordancewith leasing requirements/requests.

In the FIG. 5, the subscriber data (229) controls access by subscribersto the pop-up retail marketplace. The subscribers are given access tothe vacancy data, along with profiles of individual centers across theportfolio. Subscribers and/or subscriber data (229) can be gainedthrough partnerships with third party applications, etc. In oneembodiment, the subscribers have the opportunity to request availablespace within a certain time period.

Once applications for a retail space are received from the subscribers,the Pop-Up Retail Marketplace application sends the requests for review.A review committee selects the most appealing tenant for the space and anotice of approval is generated through the Pop-Up Retail Marketplaceapplication. The successful tenant enters into an agreement to lease thespace on a short-term basis, and also consents to having theirperformance tracked using technology, sales results, heat-mapping etc.They also consent to make their website traffic and sales analyticsavailable to the server (139) over the course of the pop-up period.Click-throughs of the website of the tenant are monitored. The tenant'sperformance is tracked against their user profile in the Pop-Up RetailMarketplace application. The Pop-Up Retail Marketplace applicationprovides authorized users with access to the performance of pop-upstores across the portfolio. Successful performance increases the ratingof the tenant, which automatically gives them preference in futuretransactions.

In one embodiment, the camera data (145) collected by the robot (101) isanalyzed to generate at least portion of the operation data (225),indicating the customer traffic level (233) in the retail space,detecting the sales events (235), such as out of business sales,clearance sales, moving sales, grand opening sales, etc.

The system as configured in FIG. 5 saves employee time which couldresult in head count and reduced expenses. It offers a new competitiveadvantage over others in the industry. Subscribers will have access toall spaces available across the shopping mall portfolio at onecentralized location. It offers a single user interface (e.g.,interactive plan (231)) for the retailer rather than having to deal withmultiple contacts, formalized way to track and monitor leads forleasing, formalized way to receive requests for marketing andfacilities, and avoids the need for a retail broker. It offers aseamless experience for the retailer where everything is completedthrough the marketplace and ERP. It uses a single brand identity topresent retail spaces to future and potential retailers.

The platform as illustrated in FIG. 5 can quickly fill empty retailspaces and generate new income, identify ‘new’ retailers who are seekingto make a transition from online-only to physical retail space—blendingthe world of online and physical, assess the performance of theseretailers, thereby establishing a database of successful retailers whomay, in the future, seek or be offered permanent retail space. Thisallows not only short term revenue but a new system to vet potentiallong term tenants. The platform provides opportunities for brand orevent partnerships with the most exciting technology and e-commercebrands that have traditionally not occupied mall space.

The platform as illustrated in FIG. 5 establishes a constant roster oftemporary activations, drive new traffic to the mall as well asencourage new traffic patterns within the mall. It offers potential newincome stream from cross-licensing the marketplace to other developersor organizations.

The platform as illustrated in FIG. 5 can be used to support a retailincubator. The single connection point between cutting edge onlineretailers and physical retail space and therefore expanding the reachbeyond traditional mall retailers and customers.

FIG. 6 shows a system to provide availability prediction and valueestimation according to one embodiment.

In FIG. 6, the server (139) uses a predictive model (243) on the trackeddata (241) (e.g., as illustrated in FIG. 5) to generate predictedavailability (247) of retail spaces in a predetermined time period inthe future, which allows the server (139) to present both retail spacesthat are currently available and retail spaces that will be available inthe future in reports (251) and marketplace (253). The prediction can bemade based on the lease expiration information in the leasing data(223), the tenant coordination data (221) and the operation data (225).

In FIG. 6, the server (139) uses a statistical formula (245) on thetracked data (241) (e.g., as illustrated in FIG. 5) to generate anestimated value (249) of each available retail space. In one embodiment,the server (139) presents both the predicted availability (247) and theestimated value (249) of retail spaces in the reports (251) and/or themarketplace (253). In one embodiment, the marketplace (253) of retailspaces is presented via the interactive plan (231) hosted on a websiteand accessible via web browsers. Alternatively, the interactive plan(231) can be implemented via mobile applications running in mobiledevices using data from the server (139).

In one embodiment, the server (139) and the database (141) provide aretailer space inventory forecasting tool that aggregates and analyzesmultiple data sources that have previously never been brought together.The system then uses an algorithm to correlate and convert that datainto a variety of actionable outcomes. For example, the tool aggregatesand correlates data from existing sources to predict temporary vacanciesacross the portfolio of retailer spaces in a physical shopping mall.This type of information would include WLMS (lease and deal data of theretailer spaces), tenant design and construction, traffic and sales,consumer trends, lease history, category performance, trade anddemographic information. Once the information is collected the algorithmpredicts inventory and value of each available space. Because of thetraffic and sales figures collected, the algorithm can rank the value ofeach potential space which would help leasing determine cost. The toolpulls data from multiple existing and new technology sources, includingbut not limited to: WLMS (lease and deal data), tenancy coordinationwebsite (tracks design and construction of new tenants andrefurbishments), retailer sales results, ShopperTrak, mall locationmanagement technology (beacons), market research software, inventorymanagement software, traffic and sales trends, searchable mall (able tosee retailers inventory levels and build a predictive model based ontheir performance), etc.

The retailer space inventory forecasting tool forecasts permanentvacancies (e.g., long term availability without a predetermined timelimit) and temporary vacancies (e.g., short time availability with apredetermined time limit that identifies the end of the vacancy period)and their monetary value to help the business generate additionalincome. It provides better knowledge of how much demand there is, whichcould in turn reduce or increase pricing depending on each market. Theapplication algorithm uses the existing data inputs to generate newpredictive data about retailers within the mall.

For example, in one variation the application analyses existing leaseexpiry dates with the progress of new design and construction within thesame space to identify potential short term vacancies. This informationis analyzed against current lease data to assign value to the temporaryspace. This information can be fed directly to a retail pop-upmarketplace.

For example, in another variation, the application analyses retailersales results against mall tracking technology to identify areas withinthe mall that are likely to fall below sales quotas and pose vacancyrisks. Those vacancy risks are, in turn, analyzed against marketresearch technology to identify which subset poses exceptional risk.

For example, in a further variation, the application analyses potentialvacancies against market trends and mall traffic to predictmerchandising opportunities for each space. The value of differentconfigurations can then be analyzed by the application to generateoptimum combinations.

Quantitative forecasting provided by the tool leads to automateddecisions to allow for additional income.

In one embodiment, the server (139) uses the data in the database (141)to identify risk in the leasing structure and assign value to theidentified risk. Examples of data that can be used to identify andquantify the risk include: space type (inline, big box, kiosk etc.),tenant type (boutique, fast fashion, food retail, restaurant etc.),occupancy ratio, leasing revenue, lease term , sales information,accounts receivable data (balance outstanding, overdue etc.), tenantfinancial health, brand sentiment/market sentiment data, and design andconstruction schedules for tenant build-outs. The data can be processedthrough a variety of statistical formulas and models, including but notlimited to: ordinary least squares, k-nearest neighbors, linearregression, logistic regression, k-means clustering, etc. The algorithmweights the data points against each other to determine the risk of atenant vacating, and calculates the financial risk associated with thatvacancy. In addition, the algorithm will look at downtimes betweentenant expiries and RCD's to identify opportunities for additionalincome.

In one embodiment, the interactive plan (231) is configured to presentplanned availability and unplanned availability. Planned availability isthe actual space availability that occurs in between tenant expiries andnew tenant RCDs. Unplanned Availability is the predicted vacancy of“at-risk” tenants that would result in lost cash flow. The server (139)is configured to compute the value of planned availability of retailerspaces based on the downtime between coming and going tenants andincorporating an achievable rental rate (e.g., rent per unit area of aretail space ($/sf)) for pop-up shops as specified by the leasingdepartment. The server (139) is configured to compute the value ofunplanned availability of retailer spaces based on the lost cash flowfor the remainder of the lease in accordance with the net present valueof the tenancy and any capital associated with the space to determineactual value of the vacancy. The loss can also be correlated withpotential financial gain, through leasing that space on a pop-up basis.

In one embodiment, the interactive plan (231) includes a virtual realitycomponent that allows the user to walk through a 3D visualrepresentation of the mall where the retail spaces are located, look atwhere the potential vacancy would be and choose based on aesthetic inaddition to financial liability.

In one embodiment, the server (136) presents the opportunity in the formof greatest to least in the values of the availabilities; and the riskin terms of most probable to default, value of lease in new potentialvacancy (NPV), or greatest risks from probability multiplied by NPV.

In one embodiment, the data provided about a tenant is used to classifythe tenant according to risk of vacancy (e.g., low, medium, or high);and when the risk is above a threshold, the leasing department isnotified to to start looking for a new tenant for the space occupied bythe current tenant.

In one embodiment, the server (139) is configured to calculated projectsbased on the risk (e.g., if the tenant leaves after 5 years of a 10 yearlease the loss will be XXX; if the tenant leaves after 9 years of a 10year lease the income loss will be ZZZ.).

In one embodiment, the server (139) is configured to generate a report(251) that specifically targeted at particular teams within themanagement of the mall (e.g., leasing, finance, project control group).

In one embodiment, new design and construction in a given space areanalyzed against vacancy data to determine if a temporary, or ‘pop-up’space may be viable. Specifically, the algorithm would draw from theestimated completion date of new tenant fit out work and correlate thatto the estimated vacancy date of an existing tenant. This would generatea financial analysis as to the potential opportunity cost ofimplementing a pop-up retail space.

In one embodiment, the marketplace is a Web based application separatefrom the data feed and the primary application. With a subscription itshows availability based on mall/center, center data and an applicationprocess. Subscribers to the Retail Marketplace are given access to thevacancy data, along with profiles of individual centers across theportfolio and provided with the opportunity to request available spacewithin a certain time period. The subscribers may be gained throughpartnerships with other organizations.

In one embodiment, the marketplace (253) is configured to receiveapplications to rent the vacated spaces. The system sends therequests/applications to a review committee for review. The reviewcommittee selects the most appealing tenant for the space and a noticeof approval is generated through the system. The successfulapplicant/tenant enters into an agreement with the mall to lease thespace on a short-term basis, and also consents to having theirperformance tracked using Westfield technology, sales results,heat-mapping etc. They also consent to make their website traffic andsales analytics available to Westfield over the course of the pop-upperiod. Click-throughs etc. are monitored. The tenant's performance istracked against their user profile in the system. The server (139) canthen access the performance of pop-up stores across the portfolio.Successful performance increases the tenant's rating, automaticallygiving them preference in future transactions.

The advantages of the marketplace (253) include: saving employee timewhich could result in head count and reduced expenses; a new competitiveadvantage over others in the industry; subscribers will have access toall spaces available across a mall portfolio at one centralizedlocation; single user interface for the retailer rather than having todeal with multiple contacts; formalized way to track and monitor leadsfor leasing; formalized way to receive requests for marketing andfacilities; the ability to avoid the use of a retail broker; a seamlessexperience for the retailer—everything is completed through themarketplace; and single brand identity to present to future andpotential retailers.

In one embodiment, the server (139) uses previous tenant defaults asbenchmarks to measure against. A k-means clustering statistical model isused to group tenants by high, medium and low risk based on salesresults/sales quotas. A linear regression statistical model is used tomeasure the probability a tenant is to default. A k-nearest neighborstatistical model is used to look and find similar tenants by a myriadof different distance measurements. If a tenant is found to be similarto struggling or defaulted tenants based on sales results/sales quotas,the tenant is determined to have the same risk as the defaulted tenants.

FIG. 7 shows a method to provide availability prediction and valueestimation according to one embodiment. For example, the method of FIG.7 can be implemented in a system illustrated in FIG. 5.

In FIG. 7, a computing system is configured to: dispatch (301) robots(101) to a plurality of spaces in an area connected via a pathway;capture (303) operation data of the robots, including photo images;combine (305) the operation data and status data of the spaces togenerate availability predictions (247) of the spaces and valueestimations (249) the spaces; and present (307) the availabilityprediction and the value estimates in a user interface (e.g., 231, 251,or 253).

In one embodiment, the computing system includes: a set of robots, adatabase, a server, and a user interface. Each respective robot in theset of robots includes: a moving mechanism configured to move the roboton a pathway; a controller configured to operate the robot within anarea having a plurality of spaces connected by the pathway; a bodyhaving a shape configured to carry items for delivery; and a cameramounted on the body and controlled by the controller to take photoimages in the area. The database stores: status data of the spaces, andoperation data of the robots dispatched to the spaces, including photoimages obtained using cameras of the robots. The server is connected tothe database and configured to combine the status data and the operationdata of the robots to generate a prediction of availability of thespaces. The user interface is configured to present the prediction.

In one embodiment, the robots are dispatched to carry items sold bystores at the spaces to a centralized location for pick up; and theoperation data includes sales data related to delivery of the items fromthe spaces to the centralized location.

In one embodiment, the robots are configured to capture the photo imageswhile being dispatched to the spaces; and the server is configured toanalyze the photo images to determine measurements of the foot trafficin the area, wherein the prediction is based at least in part on themeasurements of the foot traffic in the area.

In one embodiment, the user interface includes an interactive plan ofvacancy of spaces in the area; and the interactive plan is configured topresent the availability of the spaces and accept applications forleasing spaces predicted to be available in the area.

In one embodiment, the prediction includes availability and values ofthe spaces for rental in a period of time.

In one embodiment, the status data includes: leasing data of the spacesin the area, tenant coordination data, operation data, and subscriberdata; and the prediction is based at least in part on the leasing data,the tenant coordination data, and the operation data.

In one embodiment, the computer system is configured to perform amethod, including: providing the set of robots; dispatching the robotsto the spaces; capturing operation data of the robots, including photoimages obtained using cameras of the robots; storing, in the database,status data of the spaces and the operation data of the robots;combining, by the server connected to the database, the status data andthe operation data of the robots to generate a prediction ofavailability of the spaces; and providing a user interface to presentthe prediction.

In one embodiment, the robots are configured to carry items from thespaces to a centralized location for pick up.

In one embodiment, the operation data includes sales data related todelivery of the items from the spaces to the centralized location.

In one embodiment, the area having the spaces includes a shopping mall;and the spaces are retail spaces.

In one embodiment, the prediction includes availability of the retailspaces for rental in a period of time.

In one embodiment, the prediction includes rental values of the retailspaces in the period of time.

In one embodiment, the robots are configured to capture the photo imagesthat are indicative of foot traffic in the area; and the method furthercomprises: analyzing the photo images to determine measurements of thefoot traffic in the area, wherein the prediction is based at least inpart on the measurements of the foot traffic in the area.

In one embodiment, the status data includes: leasing data of the spacesin the area, tenant coordination data, operation data, and subscriberdata; and the prediction is based at least in part on the leasing data,the tenant coordination data, and the operation data.

In one embodiment, the prediction is generated using at least one of:least squares regression line; k-nearest neighbors; linear regression;logistic regression; and k-means clustering.

In one embodiment, the user interface includes an interactive plan ofvacancy of spaces in the area.

In one embodiment, the interactive plan is configured to present theavailability of the spaces and accept applications for leasing spacespredicted to be available in the area.

In one embodiment, the spaces predicted to be available in the area areoffered as spaces for pop-up retails.

In one embodiment, a non-transitory computer storage media storesinstructions configured to instruct a computing apparatus to perform anyof the methods disclosed herein.

FIG. 8 shows a data processing system that can be used to implement somecomponents of a robotic system according to one embodiment. For example,the data processing system of FIG. 8 can be used to implement each ofthe controller of the robot (101), the dock station (137), the server(139), and/or the database (141) discussed above.

While FIG. 8 illustrates various components of a computer system, it isnot intended to represent any particular architecture or manner ofinterconnecting the components. One embodiment may use other systemsthat have fewer or more components than those shown in FIG. 8.

In FIG. 8, the data processing system (170) includes an inter-connect(171) (e.g., bus and system core logic), which interconnects amicroprocessor(s) (173) and memory (167). The microprocessor (173) iscoupled to cache memory (179) in the example of FIG. 8.

In one embodiment, the inter-connect (171) interconnects themicroprocessor(s) (173) and the memory (167) together and alsointerconnects them to input/output (I/O) device(s) (175) via I/Ocontroller(s) (177). I/O devices (175) may include a display deviceand/or peripheral devices, such as mice, keyboards, modems, networkinterfaces, printers, scanners, video cameras and other devices known inthe art. In one embodiment, when the data processing system is a serversystem, some of the I/O devices (175), such as printers, scanners, mice,and/or keyboards, are optional.

In one embodiment, the inter-connect (171) includes one or more busesconnected to one another through various bridges, controllers and/oradapters. In one embodiment the I/O controllers (177) include a USB(Universal Serial Bus) adapter for controlling USB peripherals, and/oran IEEE-1394 bus adapter for controlling IEEE-1394 peripherals.

In one embodiment, the memory (167) includes one or more of: ROM (ReadOnly Memory), volatile RAM (Random Access Memory), and non-volatilememory, such as hard drive, flash memory, etc.

Volatile RAM is typically implemented as dynamic RAM (DRAM) whichrequires power continually in order to refresh or maintain the data inthe memory. Non-volatile memory is typically a magnetic hard drive, amagnetic optical drive, an optical drive (e.g., a DVD RAM), or othertype of memory system which maintains data even after power is removedfrom the system. The non-volatile memory may also be a random accessmemory.

The non-volatile memory can be a local device coupled directly to therest of the components in the data processing system. A non-volatilememory that is remote from the system, such as a network storage devicecoupled to the data processing system through a network interface suchas a modem or Ethernet interface, can also be used.

In the present disclosure, some functions and operations are describedas being performed by or caused by software code to simplifydescription. However, such expressions are also used to specify that thefunctions result from execution of the code/instructions by a processor,such as a microprocessor.

Alternatively, or in combination, the functions and operations asdescribed here can be implemented using special purpose circuitry, withor without software instructions, such as using Application-SpecificIntegrated Circuit (ASIC) or Field-Programmable Gate Array (FPGA).Embodiments can be implemented using hardwired circuitry withoutsoftware instructions, or in combination with software instructions.Thus, the techniques are limited neither to any specific combination ofhardware circuitry and software, nor to any particular source for theinstructions executed by the data processing system.

While one embodiment can be implemented in fully functioning computersand computer systems, various embodiments are capable of beingdistributed as a computing product in a variety of forms and are capableof being applied regardless of the particular type of machine orcomputer-readable media used to actually effect the distribution.

At least some aspects disclosed can be embodied, at least in part, insoftware. That is, the techniques may be carried out in a computersystem or other data processing system in response to its processor,such as a microprocessor, executing sequences of instructions containedin a memory, such as ROM, volatile RAM, non-volatile memory, cache or aremote storage device.

Routines executed to implement the embodiments may be implemented aspart of an operating system or a specific application, component,program, object, module or sequence of instructions referred to as“computer programs.” The computer programs typically include one or moreinstructions set at various times in various memory and storage devicesin a computer, and that, when read and executed by one or moreprocessors in a computer, cause the computer to perform operationsnecessary to execute elements involving the various aspects.

A machine readable medium can be used to store software and data whichwhen executed by a data processing system causes the system to performvarious methods. The executable software and data may be stored invarious places including for example ROM, volatile RAM, non-volatilememory and/or cache. Portions of this software and/or data may be storedin any one of these storage devices. Further, the data and instructionscan be obtained from centralized servers or peer to peer networks.Different portions of the data and instructions can be obtained fromdifferent centralized servers and/or peer to peer networks at differenttimes and in different communication sessions or in a same communicationsession. The data and instructions can be obtained in entirety prior tothe execution of the applications. Alternatively, portions of the dataand instructions can be obtained dynamically, just in time, when neededfor execution. Thus, it is not required that the data and instructionsbe on a machine readable medium in entirety at a particular instance oftime.

Examples of computer-readable media include but are not limited torecordable and non-recordable type media such as volatile andnon-volatile memory devices, read only memory (ROM), random accessmemory (RAM), flash memory devices, floppy and other removable disks,magnetic disk storage media, optical storage media (e.g., Compact DiskRead-Only Memory (CD ROMS), Digital Versatile Disks (DVDs), etc.), amongothers. The computer-readable media may store the instructions.

The instructions may also be embodied in digital and analogcommunication links for electrical, optical, acoustical or other formsof propagated signals, such as carrier waves, infrared signals, digitalsignals, etc. However, propagated signals, such as carrier waves,infrared signals, digital signals, etc. are not tangible machinereadable medium and are not configured to store instructions.

In general, a machine readable medium includes any mechanism thatprovides (i.e., stores and/or transmits) information in a formaccessible by a machine (e.g., a computer, network device, personaldigital assistant, manufacturing tool, any device with a set of one ormore processors, etc.).

In various embodiments, hardwired circuitry may be used in combinationwith software instructions to implement the techniques. Thus, thetechniques are neither limited to any specific combination of hardwarecircuitry and software nor to any particular source for the instructionsexecuted by the data processing system.

The description and drawings are illustrative and are not to beconstrued as limiting. The present disclosure is illustrative ofinventive features to enable a person skilled in the art to make and usethe techniques. Various features, as described herein, should be used incompliance with all current and future rules, laws and regulationsrelated to privacy, security, permission, consent, authorization, andothers. Numerous specific details are described to provide a thoroughunderstanding. However, in certain instances, well known or conventionaldetails are not described in order to avoid obscuring the description.References to one or an embodiment in the present disclosure are notnecessarily references to the same embodiment; and, such references meanat least one.

The use of headings herein is merely provided for ease of reference, andshall not be interpreted in any way to limit this disclosure or thefollowing claims.

Reference to “one embodiment” or “an embodiment” means that a particularfeature, structure, or characteristic described in connection with theembodiment is included in at least one embodiment of the disclosure. Theappearances of the phrase “in one embodiment” in various places in thespecification are not necessarily all referring to the same embodiment,and are not necessarily all referring to separate or alternativeembodiments mutually exclusive of other embodiments. Moreover, variousfeatures are described which may be exhibited by one embodiment and notby others. Similarly, various requirements are described which may berequirements for one embodiment but not other embodiments. Unlessexcluded by explicit description and/or apparent incompatibility, anycombination of various features described in this description is alsoincluded here. For example, the features described above in connectionwith “in one embodiment” or “in some embodiments” can be all optionallyincluded in one implementation, except where the dependency of certainfeatures on other features, as apparent from the description, may limitthe options of excluding selected features from the implementation, andincompatibility of certain features with other features, as apparentfrom the description, may limit the options of including selectedfeatures together in the implementation.

The disclosures of the above discussed patent documents are herebyincorporated herein by reference.

In the foregoing specification, the disclosure has been described withreference to specific exemplary embodiments thereof. It will be evidentthat various modifications may be made thereto without departing fromthe broader spirit and scope as set forth in the following claims. Thespecification and drawings are, accordingly, to be regarded in anillustrative sense rather than a restrictive sense.

What is claimed is:
 1. A system, comprising: a set of robots, whereineach respective robot in the set of robots includes: a moving mechanismconfigured to move the robot on a pathway; a controller configured tooperate the robot within an area having a plurality of spaces connectedby the pathway; a body having a shape configured to carry items fordelivery; and a camera mounted on the body and controlled by thecontroller to take photo images in the area; a database storing: statusdata of the spaces, and operation data of the robots dispatched to thespaces, including photo images obtained using cameras of the robots; aserver connected to the database and configured to combine the statusdata and the operation data of the robots to generate a prediction ofavailability of the spaces; and a user interface configured to presentthe prediction.
 2. The system of claim 1, wherein the robots aredispatched to carry items sold by stores at the spaces to a centralizedlocation for pick up; and the operation data includes sales data relatedto delivery of the items from the spaces to the centralized location. 3.The system of claim 1, wherein the robots are configured to capture thephoto images while being dispatched to the spaces; and the server isconfigured to analyze the photo images to determine measurements of thefoot traffic in the area, wherein the prediction is based at least inpart on the measurements of the foot traffic in the area.
 4. The systemof claim 1, wherein the user interface includes an interactive plan ofvacancy of spaces in the area; and the interactive plan is configured topresent the availability of the spaces and accept applications forleasing spaces predicted to be available in the area.
 5. The system ofclaim 1, wherein the prediction includes availability and values of thespaces for rental in a period of time.
 6. The system of claim 1, whereinthe status data includes: leasing data of the spaces in the area, tenantcoordination data, operation data, and subscriber data; and theprediction is based at least in part on the leasing data, the tenantcoordination data, and the operation data.
 7. A method, comprising:providing a set of robots, wherein each respective robot in the set ofrobots includes: a moving mechanism configured to move the robot on apathway; a controller configured to operate the robot within an areahaving a plurality of spaces connected by the pathway; a body having ashape configured to carry items for delivery; and a camera mounted onthe body and controlled by the controller to take photo images in thearea; dispatching the robots to the spaces; capturing operation data ofthe robots, including photo images obtained using cameras of the robots;storing, in a database, status data of the spaces and the operation dataof the robots; combining, by a server connected to the database, thestatus data and the operation data of the robots to generate aprediction of availability of the spaces; and providing a user interfaceto present the prediction.
 8. The method of claim 7, wherein the robotsare configured to carry items from the spaces to a centralized locationfor pick up.
 9. The method of claim 8, wherein the operation dataincludes sales data related to delivery of the items from the spaces tothe centralized location.
 10. The method of claim 9, wherein the areahaving the spaces includes a shopping mall; and the spaces are retailspaces.
 11. The method of claim 10, wherein the prediction includesavailability of the retail spaces for rental in a period of time. 12.The method of claim 11, wherein the prediction includes rental values ofthe retail spaces in the period of time.
 13. The method of claim 7,wherein the robots are configured to capture the photo images that areindicative of foot traffic in the area.
 14. The method of claim 13,further comprising: analyzing the photo images to determine measurementsof the foot traffic in the area, wherein the prediction is based atleast in part on the measurements of the foot traffic in the area. 15.The method of claim 7, wherein the status data includes: leasing data ofthe spaces in the area, tenant coordination data, operation data, andsubscriber data; and the prediction is based at least in part on theleasing data, the tenant coordination data, and the operation data. 16.The method of claim 15, wherein the prediction is generated using atleast one of: least squares regression line; k-nearest neighbors; linearregression; logistic regression; and k-means clustering.
 17. The methodof claim 7, wherein the user interface includes an interactive plan ofvacancy of spaces in the area.
 18. The method of claim 17, wherein theinteractive plan is configured to present the availability of the spacesand accept applications for leasing spaces predicted to be available inthe area.
 19. The method of claim 18, wherein the spaces predicted to beavailable in the area are offered as spaces for pop-up retails.
 20. Anon-transitory computer storage media storing instructions configured toinstruct a computing apparatus to perform the method, the methodcomprising: dispatching a set of robots to a plurality of spaces in anarea, wherein each respective robot in the set of robots includes: amoving mechanism configured to move the robot on a pathway; a controllerconfigured to operate the robot within the area having the plurality ofspaces connected by the pathway; a body having a shape configured tocarry items for delivery; and a camera mounted on the body andcontrolled by the controller to take photo images in the area; capturingoperation data of the robots, including photo images obtained usingcameras of the robots; storing, in a database, status data of the spacesand the operation data of the robots; combining, by a server connectedto the database, the status data and the operation data of the robots togenerate a prediction of availability of the spaces; and providing auser interface to present the prediction.